CN111474150A - STED super-resolution image background noise differential suppression method - Google Patents
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Abstract
The invention discloses a method for inhibiting background noise difference of an STED super-resolution image. The STED super-resolution image background noise difference suppression method comprises the steps of obtaining an STED super-resolution original fluorescence image, constructing a background fluorescence image which is adaptive to an STED intensity distribution rule from the original image by using a gray inversion transformation method according to the intensity difference between a background signal caused by peripheral loss light and a fluorescence signal in a central area of excitation light, and performing difference operation processing to improve the quality of the original super-resolution image. The super-resolution imaging device comprises an excitation light module, a loss light module, a scanning module and a fluorescence signal detection module. Meanwhile, in the specific implementation process, the invention provides the combination of the super-resolution imaging technology and the image quality evaluation technology, the light power loss is regulated and controlled, the fluorescence background noise caused by incomplete loss and the like is further reduced, the imaging quality is improved, the cost is saved, the system is simplified, and the feasibility is better.
Description
Technical Field
The invention belongs to the technical field of optical microscopy, and particularly relates to a background noise differential suppression method for an STED super-resolution image, which is used for improving the quality of the STED super-resolution image.
Background
in order to break through the Optical diffraction limit and observe biological samples even living samples with low damage, researchers have proposed a series of far-field Optical super-resolution Microscopy methods, among which Stimulated radiation loss Microscopy (STED), photo-activated positioning Microscopy (PA L M), random Optical Reconstruction Microscopy (Stochastic Optical Reconstruction Microscopy, STORM), structured light Illumination Microscopy (Structure Illumination Microscopy, SIM), super-resolution techniques have been the mainstream of the biomedical field, and related researchers have acquired the nuobel chemistry prize in 2014.
Stimulated radiation depletion microscopy is widely used because of its advantages such as real-time imaging, high resolution, etc. The principle is to irradiate two laser beams, one as exciting light and the other as loss light. The excitation light makes the electrons transit to an excited state to emit fluorescence by means of spontaneous emission, and the loss light modulated into a vortex hollow type makes the electrons at the periphery of the excitation spot return to a ground state by means of stimulated emission to suppress fluorescence emission, as shown in fig. 6. The fluorescence emission in the central area of the exciting light spot is not influenced by the damage of light consumption, fluorescence is continuously emitted through spontaneous radiation, and a super-resolution fluorescence image is obtained by collecting the fluorescence through a detector after filtering treatment. The method effectively reduces the fluorescence luminous area of the sample, compresses the point spread function of the imaging system and improves the imaging resolution.
However, STED is a tool widely used in the field of biology, and there are still many limitations in the technology. The additional Background noise of STED is an unavoidable problem at present, which has certain influence on the resolution and contrast of the image (as shown in FIG. 4 (a): Gao Pen, et al, "Background subtraction in fluorescence microscopy with stimulated emission double division," Nature Photonics 11.3(2017): 163). Background noise sources are mainly divided into two categories: firstly, the peripheral region fluorescence is not completely lost due to low loss light intensity, and the annular region has partial fluorescence residues; and secondly, the wavelength of the loss light is close to that of the excitation region, and when the light intensity of the loss light is too high, background fluorescence is generated due to an anti-Stokes excitation effect.
The basic idea of the method for suppressing the background noise of the STED super-resolution image is to perform differential optimization by acquiring a fluorescence background image, wherein the acquisition means of the background image is the key of the method. At present, many studies on the method for suppressing the STED super-resolution background noise are carried out, and most of means for acquiring the fluorescence background image are to use physical means for detection and estimation according to the generation characteristics of the background noise. Among them, the Stimulated Emission double beam depletion (sted) technique is the most representative. The STEDD principle is that three beams of pulse laser are used for irradiating a sample in a time-sharing mode, the first two beams of Gaussian excitation light and annular loss light are used for conventional STED super-resolution fluorescence imaging, the third beam of Gaussian loss light is added after specific time delay, fluorescence background noise is extracted, and the background noise is removed in an image weighting difference mode. Although STEDD has a certain effect of suppressing STED fluorescence noise, the used optical path is complicated, three-beam optical coupling and strict timing control are required, and problems such as difficulty in debugging and high cost are caused. Similar methods for detecting and estimating background images by physical means also face the same dilemma in practical operation.
Aiming at the problems of incomplete loss caused by loss light and fluorescence background noise generated by anti-stokes excitation effect, effective, simple and low-cost methods need to be developed to solve the problems.
Disclosure of Invention
The invention provides a method for inhibiting background noise by fluorescence difference, which is low in cost and does not need to increase the complexity of an optical path, in order to solve the problems of some fluorescence background noise caused by loss light in stimulated emission loss microscopy.
In the STED image, because the fluorescence loss is incomplete and the loss laser anti-Stokes excitation generates extra background noise, certain balance needs to be searched between complete loss fluorescence and anti-Stokes excitation avoidance for the light intensity of the loss light, and the light intensity of the loss light is optimized to improve the imaging effect. The STED imaging device combines a digital image analysis technology, scans a plurality of STED super-resolution fluorescence images by adjusting the light intensity of the loss light, calculates the numerical value of an image evaluation function, and determines the light intensity of the loss light capable of obtaining the optimal evaluation factor in a certain range through comparison. Scanning under the loss optical power provides an STED super-resolution image with better signal-to-noise ratio for the subsequent fluorescence background difference process, and the background image is conveniently constructed by utilizing the difference between signals and noise in the image.
In ideal STED super-resolution imaging, interference of incomplete loss and anti-Stokes excitation is eliminated, fluorescence signals in the peripheral region of the excitation light can be completely suppressed, and the point spread function of the excitation light is effectively compressed. However, in practical operation, even after the intensity of the lost light is optimized, the peripheral fluorescence signal is still difficult to be completely eliminated due to the limitation of various factors, and the STED super-resolution imaging suffers from noise. According to the intensity difference between the background signal caused by peripheral loss light and the fluorescence signal in the central area of the excitation light, the invention provides a method for constructing a background fluorescence image which is adaptive to the STED intensity distribution rule from an original image by means of gray level inversion, and differential optimization is carried out. Compared with the method for acquiring the background signal image by the aforementioned physical means, the background construction method is based on digital signal image processing, does not need a complex experimental system, and is simple and convenient to operate.
Meanwhile, the invention can be adjusted according to different images, and has good adaptability. A series of background signal images are obtained by adjusting the adjusting factors a and b in the background construction formula and are subjected to differential processing, the evaluation function values of the images are calculated one by one, so that a functional relation graph between the evaluation function Q and the adjusting factors a and b is obtained, the values a and b when the image evaluation function takes the maximum value are screened out, and the super-resolution image with the best optimization effect can be obtained.
For STED super-resolution images, the currently mainstream fluorescence background noise suppression method, such as STEDD technology, can achieve a certain effect in noise processing, but the optical path system is complex, the cost is high, strict timing management is required, and the operation difficulty is large for a general optical laboratory. The method for inhibiting the fluorescence background noise of the super-resolution image can effectively solve the problems in the prior art.
The purpose of the invention is realized by the following technical scheme:
A STED super-resolution image background noise differential suppression method comprises the following steps:
1. The laser outputs a first beam of continuous laser, after the first beam of continuous laser is filtered by the optical filter and the spatial filtering system, the first beam of continuous laser is focused on a fluorescent material through an objective lens with a high numerical aperture, and fluorescence is emitted through electron spontaneous emission transition;
2. The laser outputs a second beam of continuous laser, after the second beam of continuous laser is filtered by the optical filter and the spatial filtering system, the polarization of the second beam of continuous laser is adjusted by the half-wave plate and the 1/4 wave plate combined module, then the second beam of continuous laser is modulated by the 0-2 pi vortex phase plate to form a vortex hollow light beam, and the excitation light and the loss light are coaxially coupled by the beam splitter prism to realize the stimulated radiation loss of fluorescence;
3. Collecting the signal emitted by the fluorescent material through an objective lens, screening out the fluorescent signal through an optical filter, detecting the fluorescent signal by a photomultiplier tube (PMT) to obtain a fluorescent intensity signal at a scanning point, and scanning in XY directions to obtain a complete fluorescent super-resolution image;
4. Scanning a plurality of STED super-resolution fluorescence images by adjusting the intensity of the lost light, substituting the STED super-resolution fluorescence images into an image evaluation function for calculation, comparing and determining the intensity of the lost light when the evaluation function takes the maximum value within a certain range, and scanning under the intensity of the lost light to improve the quality of the original super-resolution fluorescence image;
5. For the super-resolution image collected under the optimal light intensity of the loss light, a background fluorescence image which is adapted to the STED intensity distribution rule is constructed from the original image by using a gray scale inversion transformation method according to the intensity difference between the background signal caused by the peripheral loss light and the fluorescence signal in the central area of the excitation light, and the quality of the super-resolution image is improved through the differential operation of the original image and the constructed background image.
6. And parameters are adjusted, and the optimization effect is improved. And adjusting parameters in the background signal construction formula, constructing different background images under different parameters, performing differential operation, and selecting the STED super-resolution image with the best optimization effect.
The details of the above steps are described in detail below.
The spatial filtering system in the step 1 is a 4f system consisting of two convex lenses, and a pinhole filter is arranged at the confocal plane to filter the TEM 00Stray light outside the mode.
The half-wave plate and 1/4 wave plate combined module in the step 1 has the function of converting linearly polarized laser into circularly polarized light. And then modulating the circularly polarized light into vortex hollow light through a 0-2 pi vortex phase plate. Compared with linearly polarized light or elliptically polarized light, the circularly polarized light is modulated by the vortex phase plate to obtain vortex hollow type loss light with more uniform energy distribution.
The principle of the action of the lost light in the step 2 is to realize stimulated radiation on the induction of high-level electrons, so that the electrons quickly return to a low energy level, and the spontaneous emission fluorescence in the overlapped region of the electrons and the light spots of the exciting light is lost.
And 2, the coupling excitation light and the loss light are used for calibrating the centers of the optical paths of the excitation light and the loss light, so that the spontaneous emission fluorescence in the overlapping area of the light spots can be effectively lost only when the centers of the two beams of light are strictly superposed, the point spread function is compressed, and the imaging resolution is improved.
And 3, the filtering screening is mainly to separate exciting light, loss light, stimulated emission fluorescence and spontaneous emission fluorescence by the principle that a dichroic mirror reflects and transmits fluorescence of different wave bands, and then further perform fluorescence filtering by a band-pass filter.
The evaluation function expression described in step 4 is as follows:
Wherein FFT represents a Fourier transform symbol, f sted(x, y) represents the super-resolution fluorescence signal intensity distribution, and W (ξ, η) represents the frequency weighting function. 
ξ, eta represents the frequency size of the frequency domain space in each direction in the image, ξ maxand η maxRepresenting the maximum frequency value in the frequency space of the respective direction, the sampling frequency being twice the maximum frequency of the signal according to the nyquist sampling law. 
ηAnd ξRepresenting the spatial size of a single pixel in an image, the sampling rate in both dimensions being the same in an acquisition two-dimensional image sensor design 
And the frequencies of the respective directions in the two-dimensional Fourier spectrum of the image can be represented 
therefore, the expression of W (xi, eta) can be further simplified into 
rξAnd r ηIndicating the magnitude of the vectors in different directions, r ξmaxAnd r ηmaxRepresenting the maximum value of vectors in different directions; the larger the value of the evaluation function is, the more high-frequency components of the image are, the stronger the fluorescence signal of the excitation central region is, and the fluorescence background noise is inhibited;
The step 5 of performing weighting operation on the fluorescence signal and further separating background noise mainly comprises the following steps:
(1) According to the intensity difference between the background signal caused by peripheral loss light and the fluorescence signal in the central area of the excitation light, a background fluorescence image which is adaptive to the STED intensity distribution rule is constructed from the original image by using a gray inversion transformation method:
Wherein a, b represent a regulatory factor, f bg(x, y) A structured fluorescence background noise intensity image, f sted(x, y) represents the intensity distribution of the original STED super-resolution fluorescence image, max represents the maximum gray value, and min represents the minimum gray value;
(2) After constructing the fluorescence background noise intensity, by means of a difference operation method: f. of sig(x,y)＝fsted(x,y)-fbg(x, y) separating out effective fluorescence signals of the excitation central region.
And 6, adjusting the parameters to improve the optimization effect, and mainly comprising the following steps of:
(1) Adjusting the adjusting factors a and b in the background image construction formula, constructing different background signal images, and acquiring corresponding difference optimization images. The adjusting factor has the function of constructing proper background noise intensity, and the specific value range is determined by the quantization level of the image gray scale;
(2) And introducing an image evaluation function, and calculating function values of the previously acquired optimized images under different adjustment factors one by one. Since the excitation center effective fluorescence signal belongs to a high-frequency signal and the background noise belongs to a low-frequency signal, the fluorescence image evaluation function can evaluate the image quality by calculating the weight of the image high-frequency signal, and the function formula is as follows:
Wherein FFT represents a Fourier transform symbol, f sig(x, y) denotes an image intensity distribution obtained by difference, and W (ξ, η) denotes a frequency weight function. 
ξ, eta represents the frequency size of the frequency domain space in each direction in the image, ξ maxand η maxRepresenting the maximum frequency value in the frequency space of the respective direction, the sampling frequency being according to the Nyquist sampling law Twice the maximum frequency of the signal. 
ηAnd ξRepresenting the spatial size of a single pixel in an image, the sampling rate in both dimensions being the same in an acquisition two-dimensional image sensor design 
And the frequencies of the respective directions in the two-dimensional Fourier spectrum of the image can be represented 
therefore, the expression of W (xi, eta) can be further simplified into 
rξAnd r ηIndicating the magnitude of the vectors in different directions, r ξmaxAnd r ηmaxRepresenting the maximum value of vectors in different directions; the larger the value of the evaluation function is, the more high-frequency components of the image are, the stronger the fluorescence signal of the excitation central region is, and the fluorescence background noise is inhibited;
(3) The functional relation graph between the image evaluation function Q and the adjustment factors a and b is obtained through the calculation, and the values a and b when the image evaluation function takes the maximum value are easy to screen, so that the STED super-resolution image with the best optimization effect is obtained.
The step 5 of constructing the background noise by performing a weighting operation using the difference between the fluorescence signal and the background noise and using the intensity value of the image as a weight is a means combined with the STED super-resolution technique. Ideally, the fluorescence signal in the peripheral region of the excitation light in STED imaging can be completely lost, but in practice, perfect effect cannot be achieved under the influence of incomplete loss and anti-Stokes excitation. Therefore, we can make the STED image obtained in the experiment more approximate to the intensity distribution of the ideal STED image by constructing the method of background noise difference optimization.
The stimulated emission loss super-resolution imaging device adopted by the invention comprises:
An excitation light module: the device comprises an excitation laser light source, a first optical filter and a first spatial filtering system;
Loss optical module: the device comprises a loss laser light source with controllable output power, a second optical filter, a second spatial filtering system, a half-wave plate, a 1/4 wave plate, a 0-2 pi vortex phase plate and a beam splitter prism;
A scanning module: consists of a scanning galvanometer, a scanning lens and a tube lens;
A fluorescence signal detection module: the system consists of a high numerical aperture objective lens, a dichroic mirror, a third optical filter, a focusing lens and a PMT imaging system.
The imaging system comprises a super-resolution imaging system and a control system. By evaluating the super-resolution fluorescence image scanned by the imaging system, the control system continuously optimizes the loss optical power, and finally obtains the original super-resolution fluorescence image with the optimal quality.
Compared with the prior art, the invention has the following advantages:
1. The automatic control technology is combined with the STED super-resolution imaging technology, an initial value, step length and range are given through an automatic control system, the light intensity of the lost light is automatically adjusted, and the automatic multi-time scanning of the super-resolution fluorescence image is realized;
2. Compared with other methods needing to set up a complex system, the method has the advantages that the super-resolution fluorescence background noise is effectively inhibited, meanwhile, the cost is low, and the operation is easy;
3. The method combines related advanced algorithm technology, introduces the calculation of image evaluation factors, and provides an evaluation standard for the quality of the super-resolution fluorescence image, thereby improving the reliability of the method.
Drawings
FIG. 1 is a schematic diagram of a stimulated radiation depletion microscopic imaging optical path according to the present invention;
FIG. 2 is a flow chart of the system control loss optical power output process of the present invention;
FIG. 3 is an algorithm processing flow of a STED super-resolution image background noise difference suppression method of the present invention;
FIG. 4(a) is a graph of raw STED super-resolved fluorescence collected;
Fig. 4(b) is a background image constructed when the fluorescence difference suppression fluorescence background noise method of the present invention is processed and the weighting values are different (a is 6, b is 5), (a is 24, and b is 9);
Fig. 4(c) is a differential image when the evaluation factor Q is 0.3186 and Q is 0.3203 after the fluorescence differential suppression fluorescence background noise method of the present invention;
FIG. 5 is a diagram illustrating an image evaluation reference factor Q calculated after different weights are set within a certain range;
Fig. 6 is a schematic diagram of the basic principle of STED super-resolution imaging.
Wherein the specific details of fig. 1 are: 1-first laser, 2-first optical filter, 3-first spatial filter system, 4-second laser, 5-second optical filter, 6-second spatial filter system, 7-half wave plate, 8-1/4 wave plate, 9-0-2 pi vortex phase plate, 10-reflector, 11-beam splitter prism, 12-scanning galvanometer, 13-scanning lens, 14-tube lens, 15-dichroic mirror, 16-high power objective, 17-third optical filter, 18-focusing lens, 19-PMT imaging system
Detailed description of the preferred embodiments
The invention is further illustrated with reference to the following figures and examples. But do not represent a limitation on the technical solution of the present invention.
The invention provides a method for inhibiting background noise by fluorescence difference, which is low in cost and does not need to add a complex optical path, in order to solve the problem of fluorescence background noise caused by loss light in stimulated emission depletion microscopy.
As shown in fig. 1 and 2, the stimulated emission depletion micro super-resolution imaging process is as follows:
(1) The continuous laser light output from the first laser 1 is used as excitation light to excite ground state electrons in the fluorescent material to an excited state of a high energy level, thereby generating spontaneous emission fluorescence. Laser output by the laser device may have partial interference signals, and the quality of light spots may have defects, so that the quality and monochromaticity of excitation light spots are improved by the first optical filter 2 and the first spatial filter system 3, and then the laser is introduced into a scanning light path through the light splitting prism 11;
(2) The continuous laser light output by the second laser 4 is used as loss light, and mainly allows excited-state electrons to return to a low energy level in a stimulated radiation mode, so that spontaneous emission fluorescence is suppressed. The light beams are shaped and filtered through the second optical filter 5 and the second spatial filter system 6, and the quality of the loss light spots is improved. And then passes through a half-wave plate 7, which changes the polarization direction of the laser light, and a 1/4 wave plate 8, where linearly polarized light is modulated into circularly polarized light when the polarization direction is at 45 deg. to the fast (slow) axis of the 1/4 wave plate. Modulating the loss light spot into a vortex hollow light beam through a 0-2 pi vortex phase plate 9, and coaxially coupling exciting light and loss light through a reflector 10 and a beam splitter prism 11;
(3) The coaxially coupled excitation light beam and loss light beam pass through the scanning galvanometer 12 to realize two-dimensional plane scanning. And then passes through the scan lens 13 and the tube lens 14, reducing aberration due to the change in the beam angle. The light beam is reflected by a dichroic mirror 15, focused by an oil lens 16 with a numerical aperture of 1.35 and an amplification factor of 60, and irradiates a sample. Then, the generated spontaneous radiation and stimulated radiation signals pass through a dichroic mirror 15 and an optical filter 17 to filter out a super-resolution fluorescence signal of the spontaneous radiation;
(4) Collecting the super-resolution fluorescence signal through a focusing lens 18, entering a PMT imaging system, recording the fluorescence signal at the position of a scanning point, and then matching the scanning galvanometer 12 with the PMT imaging system 19 to obtain a complete STED super-resolution fluorescence image;
(5) And substituting the obtained STED super-resolution fluorescence image into an image evaluation function Q to calculate a function value. Under the given initial value, step length and range, the system adjusts the output power of the second laser 4, scans and images for multiple times and calculates the corresponding image evaluation function value, and the calculation formula is as follows:
And after the light intensity of the loss light when the image evaluation function Q takes the maximum value is obtained, scanning imaging is carried out under the light intensity of the loss light, and the quality of the original super-resolution fluorescence image is improved.
As shown in fig. 3, based on the intensity difference between the fluorescence signal and the background noise region in the STED super-resolution image, a fluorescence background noise image is constructed according to the image gray-scale value weighting operation, and the fluorescence super-resolution image with a high signal-to-noise ratio is further obtained through the background image constructed by difference, which is implemented as follows:
(1) Constructing a background fluorescence image which is adaptive to the STED intensity distribution rule from the original image:
(2) And (3) separating fluorescence signals of the excitation center by a differential operation mode:
fsig(x,y)＝fsted(x,y)-fbg(x,y)
(4) Adjusting the adjusting factors a and b in the background image construction formula, constructing different background signal images, and acquiring corresponding difference optimization images. (ii) a
(5) Introducing an image evaluation function, and calculating function values of the obtained optimized images under different adjustment factors one by one:
(6) The functional relation graph between the image evaluation function Q and the adjustment factors a and b is obtained through the calculation, and the values a and b when the image evaluation function takes the maximum value are easy to screen, so that the STED super-resolution image with the best optimization effect is obtained.
As shown in figure 4(a), mGarnet-RITA fusion protein to cytoskeleton labeling, and imaging to obtain the original STED super-resolution fluorescence image. As shown in fig. 4(b), different adjustment factors a, b are set to construct the fluorescence background noise. As shown in fig. 4(c), fluorescence signals in the excitation center region are separated by a differential operation method. The original STED fluorescence image can be seen from the experimental image to have stronger fluorescence background noise, and the fluorescence background noise is inhibited after the treatment of the method.
As shown in fig. 5, it can be known that the use of different adjustment factors a and b has a large influence on the image after the difference processing by calculating the image evaluation function. By optimizing the adjustment factor, the STED super-resolution image quality can be further improved.
The method for suppressing the background noise difference of the STED super-resolution image according to the present invention may be changed or modified, but is not limited to the above-described embodiments. In conclusion, the scope of the present invention should include those changes, substitutions and alterations as would be apparent to one of ordinary skill in the art.
Claims (3)
1. A STED super-resolution image background noise differential suppression method comprises the following steps:
S1 simulates and constructs a background signal fluorescence image, and performs a difference operation. Aiming at the background fluorescence signals generated by incomplete loss of the loss light and anti-Stokes excitation in the peripheral area after overlapping of Gaussian excitation light and vortex hollow loss light in the traditional STED super-resolution imaging, a background fluorescence image which is adaptive to the STED intensity distribution rule is constructed from an original image by using a gray scale inversion transformation method according to the intensity difference between the background signals caused by the peripheral loss light and the fluorescence signals in the central area of the excitation light, and the STED super-resolution image with high contrast can be obtained after differential operation of the original image and the background fluorescence image.
S2 adjusting parameters to improve the optimization effect. And adjusting parameters in the background signal construction formula, constructing different background images under different parameters, performing differential operation, and selecting the STED super-resolution image with the best optimization effect. And the optimization effect is quantitatively evaluated by an image evaluation function for calculating the weight of the high-frequency signal of the image.
2. The method for suppressing the background noise difference of the STED super-resolution image according to claim 1, wherein in the step S1, the simulation of constructing the background signal fluorescence image and performing the difference optimization mainly comprises the following steps:
S1.1, based on the intensity difference between the background signal caused by STED peripheral loss light and the fluorescence signal in the central region of the excitation light, the intensity value of the image is used as the weight to perform weighting operation on the original image by a gray inversion transformation method, and a background fluorescence image which is adaptive to the STED intensity distribution rule is constructed from the original image, wherein the operation method comprises the following steps:
Wherein a, b represent a regulatory factor, f bg(x, y) A structured fluorescence background noise intensity image, f sted(x, y) represents the intensity distribution of the original STED super-resolution fluorescence image, max represents the maximum gray value, and min represents the minimum gray value;
S1.2, after the fluorescence background noise intensity is constructed, the difference operation is carried out on the original image and the background signal image according to the following formula:
fsig(x,y)＝fsted(x,y)-fbg(x,y)
Separating effective fluorescence signals to obtain a high-contrast STED super-resolution image.
3. The method for suppressing the background noise difference of the STED super-resolution image according to claim 1, wherein the step S2 is performed by adjusting parameters to improve the optimization effect, and the method mainly comprises the following steps:
And S2.1, adjusting the adjusting factors a and b in the formula S1.1, constructing background signal images under different conditions, and acquiring corresponding difference optimization images. The adjusting factor has the function of constructing proper background noise intensity, and the specific value range is determined by the quantization level of the image gray scale;
And S2.2, introducing an image evaluation function, and calculating function values of the optimized images under different adjustment factors acquired in the S2.1 one by one. Since the excitation center effective fluorescence signal belongs to a high-frequency signal and the background noise belongs to a low-frequency signal, the fluorescence image evaluation function can evaluate the image quality by calculating the weight of the image high-frequency signal, and the function formula is as follows:
Wherein FFT represents a Fourier transform symbol, f sig(x, y) represents an image intensity distribution obtained by difference, and W (ξ, η) represents a frequency weight function. 
ξ, eta represents the frequency size of the frequency domain space in each direction in the image, ξ maxand η maxRepresenting the maximum frequency value in the frequency space of the respective direction, the sampling frequency being twice the maximum frequency of the signal according to the nyquist sampling law. 
ηAnd ξRepresenting the spatial size of a single pixel in an image, the sampling rate in both dimensions being the same in an acquisition two-dimensional image sensor design 
And the frequencies of the respective directions in the two-dimensional Fourier spectrum of the image can be represented 
therefore, the expression of W (xi, eta) can be further simplified into 
rξAnd r ηIndicating the magnitude of the vectors in different directions, r ξmaxAnd r ηmaxRepresenting the maximum value of vectors in different directions; the larger the value of the evaluation function is, the more high-frequency components of the image are, the stronger the fluorescence signal of the excitation central region is, and the fluorescence background noise is inhibited;
And S2.3, obtaining a functional relation graph between the image evaluation function Q and the adjustment factors a and b through the calculation of S2.2, and easily screening the values a and b when the image evaluation function takes the maximum value, so as to obtain the STED super-resolution image with the best optimization effect.
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